Molecular epidemiology of clinically relevant single and mixed species in a Malaysian tertiary care hospital

Background and Purpose: The increasing rate of opportunistic infections caused by Candida and other yeasts is becoming a major health concern worldwide. However, systematic data on the epidemiology and the yeast species infections in Malaysia is still limited. In this regard, the present research aimed to identify pathogenic yeasts utilizing an economically practical and easily available molecular technique and evaluate the prevalence of pathogenic yeasts in a Malaysian tertiary care hospital. Materials and Methods: Yeast isolates were collected from Sultan Abdul Halim Hospital, Kedah, Malaysia, from October 2020 to October 2021. Molecular identification of the isolates was performed by one enzyme-based polymerase chain reaction-restriction fragment length polymorphism method. Results: Candida albicans was the most prevalent species, accounting for 120 isolates (59%) in total. The most prevalent non-albicans Candida species were C. tropicalis (n=33, 16%), C. krusei (Pichia kudriavzevii) (n=12, 5.8%), C. glabrata (n=12, 5.8%), and C. parapsilosis (n=6, 3%). Other unusual Candida species were C. guilliermondii (2), C. metapsilosis (2), C. orthopsilosis (1), C. lusitaniae (1), C. rugosa (1), C. haemulonii (1), C. bracarensis (1), and C. dubliniensis (1). Moreover, Talaromyces marneffei (1), Kodamaea ohmeri (1), Cryptococcus neoformans (3), and Cryptococcus laurentii (1) were among the other yeasts identified. Conclusion: The Molecular technique used in this study identified 96% of isolates, including mixed species. According to the findings, the most prevalent species are C. albicans, C. tropicalis, C. krusei, and C. glabrata.


Introduction
he Candida genus includes around 154 species, six of which are most frequently isolated in human infections, namely C. tropicalis, C. glabrata, C. parapsilosis, C. krusei (Pichia kudriavzevii), and C. lusitaniae.However, the diversity of species seen in infections is growing, and additional formerly uncommon species are now more likely to arise [1].For example, C. auris, a multidrug-resistant pathogen, has recently become known worldwide [2].
Every year, more than 250,000 people are affected by invasive candidiasis, with a death rate of more than 70% [3,4].According to the statistics, candiduria kills patients who are hospitalized in the intensive care unit (ICU) more than other patients [5][6][7][8][9][10].In many regions of the world, including Malaysia, the real epidemiology of Candida-based infections, their distribution, and management at the species level are missing.Identification of infections at the species level is crucial since each species has a specific antifungal drug susceptibility pattern [11].Another compelling reason to identify at the species level is the recent emergence of C. auris and other emerging species.
Candida auris is a multi-drug-resistant pathogen and appears to be transferred from infected or colonized patients in healthcare settings; unlike most other species, C. auris has caused several significant outbreaks in hospitals [11,12].Therefore, as the presence of C. auris at any place poses a risk of transmission, it is crucial to identify the species to conduct infection control measures when needed.Therefore, we must explore methods that can be more sensitive and specific and that can rapidly and accurately identify fungal infections up to the species level.Traditional methods of identification are timeconsuming and frequently result in incorrect identification.The molecular approach to diagnosis is fast becoming the accepted standard for many bacterial and viral infections, especially for the identification of isolates growing in pure cultures.However, despite being around for more than a decade, molecular tests are still not utilized as a diagnostic tool to identify fungal pathogens.
There is no known molecular method that can be applied universally and still be economically feasible.This problem also makes it difficult to find remedies that are acceptable to the Food and Drug Administration (FDA).A global shortage of medical mycologists and research in this sector limits molecular diagnostics for fungal diseases.
The current study aimed to identify yeast isolates up to the species level using an economically feasible and generally available molecular approach and find out the prevalence of common pathogenic yeasts in a tertiary care hospital in northern Malaysia.

Study design and sampling
This cross-sectional study was performed using a convenience sampling technique.The sample size was calculated using the following formula: n=

Identification of yeasts
The isolates collected from the hospital were subcultured on Sabouraud dextrose agar (Merck, Germany) and incubated at 30 °C for 48 h.Subsequently, the cultures were saved in 80% glycerol stocks at -80°.In this study, five standard strains, Candida (ATCC 10231), C. parapsilosis (ATCC 90018), C. glabrata (ATCC 15126), C. tropicalis (ATCC 1369), and C. auris (CDC B11903), were used as quality control.Initially, the yeasts were identified using microscopy and Candida Differential Agar Media (Himedia) [13].After initial identification, the isolates were subjected to the molecular method of polymerase chain reactionrestriction fragment length polymorphism (PCR-RFLP) [14,15].The yeast DNA was extracted using the MasterPure Yeast DNA Purification Kit (Lucigen, USA).Cells were lysed non-enzymatically at 65 °C, followed by protein precipitation, nucleic acid precipitation, and DNA resuspension.The PCR-RFLP was performed based on a standard method described by Mirhendi et al. [14,15], with a few modifications.The referenced study used universal primers ITS1 (5-TCCGTAGGTGAACCTGCGG-3), and ITS4 (5-TCCTCCGCTTATTGATATGC-3) purchased from Integrated DNA Technologies in Singapore to amplify the ITS1-5.8SrRNA ITS2 regions.The final PCR volume was 50 µL.Each reaction comprised 25 µL of 2 X PCR master mixes (Green Taq Mix, Vazyme), 1 µL of each primer (0.2 µM), 3 µL of DNA template, and 20 µL of nucleotide-free water.Conditions for PCR were as follows: initial denaturation at 95 °C for 3 min, followed by 35 cycles of denaturation for 30 s, annealing at 56 °C for 45 s, and extension for 1 min, with a final extension at 72 °C for 5 min [14,15].The amplified PCR products were digested with FastDigest MspI (Thermo Fisher Scientific, USA): 10 µL PCR product, 17 µL nuclease-free water, 2 µL 10× buffer, and 1 µL enzyme were mixed and incubated at 37 °C for 30 min.The PCR and RFLP products were separated on a 1.5% agarose gel in Tris-borate-EDTA buffer for 45 min at 100 V and visualized by staining with ethidium bromide.

Interpretation of restriction fragment length polymorphism results
For molecular identification of different yeast species, the already described PCR-RFLP profiles were used [14,15].The identification was made by comparing the RFLP product band pattern with reference band patterns and sizes published by the author of the method [15,16].The band sizes were also confirmed by the standard curve of the ladder using the formula in Microsoft Excel.The reference sizes of the PCR and RFLP products for  1.Five reference strains were also subjected to PCR-RFLP to determine whether the profiles described in the reference method were similar to those obtained on an experimental basis.

Services availed for the identification of unknown species Sequencing
The services of 'Apical Scientific, Malaysia' were used for sequencing the unknown species.They used Sanger sequencing with the ABI PRISM 3730xl Genetic Analyzer, developed by Applied Biosystems, USA.The chemistry that they use for sequencing purposes is the BigDye® Terminator v3.1 Cycle Sequencing Kit.Furthermore, regarding the protocol of sequencing, it is a standard protocol used for preparing the sample for sequencing.

Matrix-assisted laser desorption ionization-time-offlight (Bruker)
To confirm the identification of a few species, the matrixassisted laser desorption ionization-time-of-flight (MALDI-TOF) services provided by Sultan Abdul Halim Hospital were used.A portion of the colony of the microbe was placed on the sample target and overlapped with the matrix.In biotyping, the mass spectra of expressed proteins are analyzed by dedicated software and compared with stored profiles to determine species.

Statistical analysis
Statistical analysis was performed using SPSS and Excel software.The collected data were documented in Microsoft Excel (Microsoft Corp., USA) before being transferred to SPSS (version 20, IBM, USA) for analysis.Furthermore, descriptive statistics were used to determine the frequencies of the species distributions.The relationship between species and specimen sources was found using the Chi-square test.

Results
The hospital received 206 yeast isolates, which were recovered from 10 distinct types of clinical specimens from October 2020 to October 2021.Most of the yeast isolates were isolated from urine (n=104).Other isolates were isolated from blood (52), high vaginal swabs (45), ear discharge (2), tracheal aspirate (2), tissue (2), skin (1), nail (1), sputum (1), and cerebrospinal fluid (1), respectively.Tables 3 and 4 tabulate the relationship between the distribution of different species and different types of clinical samples.Results of chi-square tests revealed that there is a significant relationship between Candida species and sources of specimen collection.Most of the Candida species were found in the urine specimen, X 2 (15, N=206) =46.5 (P<0.001).This molecular method alone could not tell the difference between C. albicans and C. dubliniensis, nor could it tell the difference between C. parapsilosis complex species (C.parapsilosis, C. metapsilosis, and C. orthopsilosis).The MALDI-TOF and sequencing methods were used to confirm these species.The identification of T. marneffei and K. ohmeri was also confirmed by MALDI-TOF and sequencing.Even though these two species have shown a specific PCR and RFLP band pattern (Figure 1), this pattern has not been previously reported and therefore requires additional validation.According to the prevalence formula, the prevalence of yeast infections in Sultan Abdul Halim Hospital for a certain year was 0.4%.

Discussion
This study is the first molecular epidemiologic investigation of the species distribution profile of clinically relevant species in the northern part of Malaysia.The distribution of C. albicans in this investigation is consistent with previous research.However, the trend of non-albicans Candida species in this study differs from those of the previous research.In the present study, C. tropicalis was the second most common species, followed by C. glabrata and C. parapsilosis in the third and fourth places, respectively.In most other studies, C. parapsilosis and C. glabrata were the second and third most prevalent non-albicans Candida infections [6,[17][18][19][20].In an Iranian study, a similar pattern of C. tropicalis was found (15).Candida krusei was discovered at the same frequency (second) as C. tropicalis in the present study.However, in previous studies, it was consistently ranked fifth in frequency [6,15,[17][18][19][20].We also identified two unusual and rare yeast species, namely T. marneffei and K. ohmeri.One isolate was identified as T. marneffei, which was extracted from a blood sample of an HIV patient.Talaromyces marneffei is a dimorphic opportunistic fungus mostly found in Southeast Asian nations and causes widespread, life-threatening illnesses.Very little published data on this yeast is available in Malaysia.Only two case reports from Malaysia have reported this infection [21,22].One isolate was identified as K. ohmeri in the current study, isolated from the blood of a COVID-19 patient.It is also a life-threatening illness that is seldom encountered.The first case of K. ohmeri fungemia was reported in the United States in 1998; however, since then, only 12 instances have been recorded there.At the same time, only three documented cases have been reported from various locations in Malaysia [23][24][25].A significant concern in all three cases was that the patients suffered from poorly controlled diabetes mellitus.However, this is the first reported case of K. ohmeri in COVID-19 patients in Malaysia with no Diabetes history.The patient could not survive and died after 1 month of treatment in the ICU.We also identified six yeast cultures, a mixture of species, with the molecular method used in this study.Mixed yeasts can go undetected by routine identification methods.Misidentifications and underreporting of cases can be the cause of such fatal situations.The rate of mixed yeast infections and frequent species combinations in this study was similar to those of previous studies from other parts of the world.In most investigations, the rate of MY infections was around 3-4%, with C. albicans and C. glabrata being the most prevalent combinations [26][27][28][29].Candida species are frequently cultured out of urinary samples.Candiduria a common clinical finding, especially in hospitalized patients.In most situations, especially in adults, candiduria reflects colonization; however, this determination requires additional information regarding symptoms and clinical context.Risk factors for Candida infections in the urinary tract include female gender, extremes of age, diabetes mellitus, long-term hospitalization, ICU admission, recent use of broad-spectrum antibiotics or immunesuppressants, dysfunction of the bladder, urinary stasis, nephrolithiasis, transplantation, congenital or structural abnormalities of the urinary tract, and catheterization [30].The proposed "one enzyme PCR-RFLP" molecular method utilized in this work has the potential to detect almost all clinically significant yeasts as well as mixed culture infections.After acquiring culture on plates, it took 6 h to report the findings.Furthermore, this method does not require buying expensive equipment or media.It can be implemented in any diagnostic lab or hospital that already has a PCR setup.

Conclusion
Based on the results, the most common Candida species are C. albicans, C. tropicalis, C. krusei, and C. glabrata.This Molecular technique correctly identified 96% of the isolates tested, including mixed species and other rare species.As a result, it is possible to conclude that the PCR-RFLP technique used in this study can be a useful tool in routine laboratories for the identification of fungal infections.
[DEFF*Np(1-p)]/[(d2/Z2 1-α/2*(N-1)+p*(1-p)]. Culture plates of all yeasts, including Candida species, were collected from the Pathology Department of Sultan Abdul Halim Hospital, Kedah, Malaysia, from October 2020 to October 2021.The samples were further processed for experiments, and the results were analyzed in the Microbiology and Molecular Biology Laboratories of the university.All positive yeast cultures, which were received from October 2020 to 2021 in the pathology lab, were included in the study, except molds.Yeast isolates were collected from different clinical specimens (urine, blood, high vaginal swabs, and tracheal aspirates) in Sultan Abdul Halim Hospital, from October 2020 to October 2021.The Medical Research Ethics Committee of AIMST University, Kedah, Malaysia, and the Medical Research and Ethics Committee, Ministry of Health of Malaysia, approved this study under the code ID NMRR-20-1588-53243 (IIR).

Table 3 .
Yeast species distribution with respect to specimen sources

Table 4 .
Relationship between different species and different types of clinical specimen